Compositions and methods for augmenting the nasal microbiome

ABSTRACT

Embodiments of the invention provide a method of reducing colonization of a subject&#39;s anterior nares and/or nasal cavity by a microorganism (e.g., Staphylococcus aureus). In some aspects, the method may include administering a pharmaceutical composition to the subject, wherein the pharmaceutical composition comprises a therapeutically effective amount of at least one probiotic.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is the U.S. National Stage of InternationalApplication No. PCT/US2016/029171 filed Apr. 25, 2016, which claims thebenefit of U.S. Provisional Application No. 62/152,547, filed Apr. 24,2015, the contents of each of which are incorporated herein by referencein their entireties.

INCORPORATION-BY-REFERENCE OF MATERIAL ELECTRONICALLY FILED

The official copy of the sequence listing is submitted electronicallyvia EFS-Web as an ASCII-formatted sequence listing with a file named“150410_236_Probiotic_ST25.txt” created on Apr. 19, 2016, and having asize of 2 kilobytes, and is filed concurrently with the specification.The sequence listing contained in this ASCII-formatted document is partof the specification and is herein incorporated by reference in itsentirety.

FIELD OF INVENTION

The present invention is generally directed to compositions and methodsfor augmenting the nasal microbiome and more specifically directed toecompositions and methods for using probiotic candidates for controllingthe growth (e.g., treating) of potentially pathogenic microorganismswithin the anterior nares and/or nasal cavity.

BACKGROUND OF THE INVENTION

The human microbiome can play a key role in host susceptibility topathogens, including in the nasal cavity, a site favored byStaphylococcus aureus. However, it is still unknown what determines ourresident nasal microbiota—the host or the environment—and the influenceof these interactions among nasal bacteria with respect to S. aureuscolonization.

Strain typing indicates that 80-85% of S. aureus bacteremia cases arecaused by the same strains carried in patients' anterior nares. The datalinking persistent S. aureus nasal carriage to increased risk forinvasive staphylococcal infections are robust, but we know little aboutthe determinants of S. aureus nasal carriage. Likewise, there is acritical need for alternative S. aureus decolonization strategies thatprovide greater long-term success, without selecting formultidrug-resistant S. aureus strains or disrupting the endogenous nasalmicrobiota. Four factors are key to understanding S. aureus nasalcarriage—(i) host characteristics, (ii) environmental exposure, (iii) S.aureus colonization factors, and (iv) nasal microbiota. While there areknown host risk factors (e.g., age), our work with the twins has shownthat host genetics have limited impact on S. aureus nasal carriage.Likewise, human challenge studies suggest that exposure and S. aureuscolonization factors are not sufficient to establish S. aureus carriage,as S. aureus strains from persistent carriers failed to colonizenon-carriers.

In preliminary studies, the investigators found that the absoluteabundances of specific nasal commensals can predict S. aureus carriage.Specifically, the investigators found that Dolosigranulum andSimonsiella colonization was significantly associated with S. aureusexclusion, while Propionibacterium acnes and Corynebacteriumcolonization was negatively correlated with the absolute abundance of S.aureus in the nasal cavity. As such, there is a need to investigatecompositions and methods for treating, preventing, reducing, and/oreliminating S. aureus colonization of the nasal cavities to precludepotential downstream infections.

SUMMARY

In some embodiments, the invention may comprise a method of reducingcolonization of a subject's anterior nares and/or nasal cavity by amicroorganism. For example, the microorganism may be a potentiallypathogenic organism, such as Staphylococcus aureus (e.g.,methicillin-resistant Staphylococcus aureus). In some aspects, themethod may include administering a pharmaceutical composition to thesubject, wherein the pharmaceutical composition comprises atherapeutically effective amount of at least one probiotic. In someaspects, the pharmaceutical composition may include at least onepharmaceutically acceptable carrier. Moreover, the at least oneprobiotic may comprise at least one organism, such as a probioticorganism. For example, the probiotic organism may comprise at least oneof Dolosigranulum species and Simonsiella species.

Other embodiments of the invention may comprise a method of treating ina subject nasal colonization by at least one pathogenic organism. Forexample, the pathogenic organism may comprise Staphylococcus aureus(e.g., methicillin-resistant Staphylococcus aureus). In someembodiments, the method may include administering a pharmaceuticalcomposition to the subject, wherein the pharmaceutical compositioncomprises a therapeutically effective amount of at least one probiotic.In some aspects, the pharmaceutical composition may include at least onepharmaceutically acceptable carrier. For example, the pharmaceuticallyacceptable carrier may comprise a growth medium to sustain the at leastone probiotic prior to administration to the subject. Moreover, the atleast one probiotic may comprise at least one organism, such as aprobiotic organism. For example, the probiotic organism may comprise atleast one of Dolosigranulum species and Simonsiella species. Inaddition, in some aspects, the method may also include administering atherapeutically effective amount of at least one antibiotic (e.g.,mupirocin). Further, in some embodiments, the method may includeintranasally administering the pharmaceutical composition to thesubject.

In other embodiments, the invention may include a pharmaceuticalcomposition comprising at least one probiotic organism. For example, theat least one probiotic organism can be selected from the groupconsisting of Dolosigranulum species and Simonsiella species. In someaspects, the pharmaceutical composition is formulated for intranasaladministration. In some aspects, the pharmaceutical composition mayinclude at least one pharmaceutically acceptable carrier. For example,the pharmaceutically acceptable carrier may comprise a growth medium tosustain the at least one probiotic organism.

Additional objectives, advantages and novel features will be set forthin the description which follows or will become apparent to thoseskilled in the art upon examination of the drawings and detaileddescription which follows.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-C depict the seven nasal microbiome community state types(CSTs) and their respective bacterial density shown in boxplots andcomposition (in bacterial 16S rRNA gene copies per swab) shown inheatmap visualization and non-metric multidimensional scaling (nMDS)ordination plot. In the boxplots in FIG. 1A, the box of each boxplotdenotes the inter-quartile range (Q2-Q3) and the corresponding median,whereas the whiskers signifies the upper and lower 1.5×IQR and the opencircles denote outliers beyond the whiskers. The difference in bacterialdensity was significantly greater across than within CSTs (ANOVAp<0.001). In particular, CST3 had significantly lower bacterial densitythan all other CSTs except CST4, and CST2 had significantly higher thanall other CSTs except CST6 (two-tailed Wilcoxon Rank-Sum p<0.05) (FIG.1A). In the heatmap visualization in FIG. 1B, each participant's nasalmicrobiota is represented in a single column and each nasal bacterialtaxon's proportional abundance is shown by row according to the colorkey to the left. The nasal microbiota is grouped by CSTs, as indicatedby the CST color bar above. The S. aureus culture result of eachparticipant is noted by the green/black color bar above. In the nMDSordination plot in FIG. 1C, each participant's nasal microbiota (inproportional abundance) is represented by a single data point, and datapoints that are closer being more similar in composition than pointsthat are farther apart. The centroids and 95% confidence ellipse foreach CST is shown.

FIG. 2A-C shows that nasal microbiome is not fixed by host genetics andtherefore can be modified through external manipulations such asprobiotics. Specifically, the FIG. 2A-C depict data illustrating thelimited correlation of nasal microbiota composition among monozygoticand among same-sex and opposite-sex dizygotic twin pairs in non-metricmultidimensional scaling (nMDS) ordination plots. In nMDS plots, eachdata point represents an individual's microbiota at one time point. Eachtwin pair is connected by a solid line, which showed that the nasalmicrobiota in monozygotic twin pairs (FIG. 2A) had low CST concordance,as same-sex (FIG. 2B) and opposite-sex dizygotic twins (FIG. 2C).

FIGS. 3A-3C shows that total nasal bacterial density variessignificantly based on sex and therefore men and women will likelyrequire different probiotic formulations. Specifically FIG. 3A-3C depictnasal bacterial density and S. aureus absolute abundance by sex and therelationship between S. aureus absolute abundance and S. aureus culture.The scatterplot shows the higher nasal bacterial density in men thanwomen (FIG. 3A). Individuals (non-CST1) with detectable S. aureus nasalcolonization could be divided based on S. aureus absolute abundance intofour categories. Women were more likely to have the two lowestcategories of S. aureus absolute abundance (i.e., <10⁴ and 10⁴-10⁵),whereas men are more likely to have the middle two categories (i.e.,10⁴-10⁵ and 10⁵-10⁶)(FIG. 3B). Culture outcome was strongly linked to S.aureus absolute abundance, and each ten-fold increase in S. aureusabsolute abundance increases the probability of positive S. aureusculture by 30%, which suggests that the sex difference in S. aureusabsolute abundance might explain the lower S. aureus culture rates inwomen than men (FIG. 3C).

FIGS. 4A-B depict rates of S. aureus nasal colonization by sequencingand by culture and S. aureus absolute abundance for the seven nasalCSTs. Rate of S. aureus nasal colonization varied across nasal CSTs asdetected based on sequencing and by culture. In general, sequencingdetection revealed higher S. aureus prevalence than culturing, except inCST2, where sequencing had lower sensitivity, most likely due toinsufficient reads in the context of high total bacterial density (FIG.4A). As shown by boxplots of S. aureus absolute abundance, CST1 and CST6had the highest S. aureus absolute abundance, whereas CST5 had thelowest S. aureus absolute abundance (FIG. 4B).

FIGS. 5A-B depict results from decision tree model derivation andvalidation showing threshold-dependent relationships between theabsolute abundances of nasal commensals and S. aureus presence/absence.A model predicting S. aureus presence/absence was derived using arandomly drawn group of 100 (FIG. 5A); it showed that the mostinformative split was a threshold of 1.2×10⁶ Dolosigranulum 16S rRNAgene copies per swab. Having above-threshold Dolosigranulum predictsabsence of S. aureus (n=4/25, 16.0%), as compared to S. aureus nasalcolonization rate in the overall derivation group (n=56/100, 56%).Simonsiella had a similarly negative relationship to S. aureus, whereamong individuals who had below-threshold abundance of Dolosigranulum,having ≥1.1×10⁵ Simonsiella predicts absence of S. aureus (n=1/7,14.3%). Validation testing using 10 randomly drawn groups of 100supported that threshold-based relationships between Dolosigranulum,Simonsiella, P. granulosum, and S. epidermidis and S. aureuspresence/absence (FIG. 5B).

FIGS. 6A-B depict results from decision tree model derivation andvalidation showing threshold-dependent relationships between theabsolute abundances of nasal commensals and S. aureus. Absoluteabundance of S. aureus can be divided into five categories, ranging fromCategory 1 (i.e., not detected) to Category 5 (i.e., 10⁶-10⁷ S. aureus16S rRNA gene absolute abundance). The S. aureus absolute abundancecategories for the derivation group of 100 are as shown (FIG. 6B), whichwas used to build a model to predict S. aureus absolute abundance (FIG.6A). The model showed that the most informative split was a threshold of1.2×10⁶ Dolosigranulum 16S rRNA gene copies per swab, which predictedCategory 1 (n=21/25, 84.0%) (Node 1 Left). Corynebacterium had asimilarly negative relationship to S. aureus absolute abundance, whereamong individuals who had below-threshold abundance of Dolosigranulumand P. acnes, having ≥3.5×10⁵ Corynebacterium predicts low S. aureusabsolute abundance, i.e., Category 2 (Node 3 Left), whereas having<3.5×10⁵ Corynebacterium predicts high S. aureus absolute abundance,i.e., Category 5 (Node 3 Right). In contrast, absolute abundance of S.epidermidis and S. aureus were positively correlated among individualswith low Dolosigranulum and high P. acnes. Validation testing using 10randomly drawn groups of 100 supported that threshold-basedrelationships between Dolosigranulum, P. acnes, S. epidermidis,Corynebacterium and S. aureus absolute abundance (FIG. 6C).

FIG. 7 depicts a species-level classifier pipeline.

The headings used in the figures should not be interpreted to limit thescope of the claims.

DETAILED DESCRIPTION

Embodiments of the invention provide compositions and methods for theaugmentation of the presence of one or more organisms on, near, adjacentto, or in a subject. For example, in some embodiments of the invention,the compositions and methods can be used to control, treat, reduce,eliminate, and/or prevent the colonization by an organism of a portionof a subject. Specifically, some aspects of the present invention can beused to control, treat, reduce, eliminate, and/or prevent the growth oforganisms that may potentially negatively impact the health of thesubject. Moreover, in some embodiments, the compositions and methods ofthe instant invention can be used to in particular locations of thesubject, such as the anterior nares and/or nasal cavity.

Moreover, in some embodiments, the compositions and methods can be usedto treat, reduce, eliminate, and/or prevent the colonization bypotentially pathogenic microorganisms in portions of the subject. Forexample, in some aspects the potentially pathogenic microorganisms maybe at least one of bacteria, viral particles, parasites (e.g.,prokaryotic and eukaryotic parasitic organisms), etc. In particular, themicroorganism may be gram positive and/or gram negative bacteria. By wayof example only, in some embodiments, the organism may be a grampositive bacterium, such as Staphylococcus aureus.

In some embodiments, the subject can be an animal, such as a humanbeing, a veterinary animal, such as a companion animal or livestock, orany other animal amenable to the treatment compositions and methodsdescribed herein. A subject includes any human or non-human mammal,including for example: a primate, cow, horse, pig, sheep, goat, dog,cat, or rodent, capable of being colonized by other organisms.

Some embodiments of the invention may encompass the development andadministration of one or more pharmaceutical compositions. In someaspects, the pharmaceutical compositions may include one or moreprobiotics. As used herein, “probiotics” are active ingredients thathave been known to be associated with positive health benefits inindividuals, subjects, patients, etc. that receive the probiotics. Insome aspects, probiotics refer to organisms, such as bacteria and yeast,which provide health benefits when administered to a subject. Forexample, as detailed herein, the investigators have made the unexpecteddetermination that administration of probiotic organisms, such asDolosigranulum species and Simonsiella species, can affect thecolonization of a subject by potentially pathogenic microorganisms, suchas S. aureus.

The invention further encompasses pharmaceutical compositions thatinclude one or more probiotics/probiotic organisms (e.g., bacteria) asingredients. By way of example only, in some aspects, the probioticorganisms may comprise at least one of Dolosigranulum species andSimonsiella species. In other embodiments, the probiotic organisms maycomprise any other bacteria, yeast, or other organisms that are capableof providing the desired health benefits of controlling, treating,reducing, eliminating, and/or preventing the colonization of portions ofthe subject (e.g., the nasal cavities/anterior nares).

In one aspect, the Dolosigranulum species are characterized as follows:Firmicutes/“Bacilli”/“Lactobacillales”/“Carnobacteriaceae”/Dolosigranulum.Cells are ovoid, occurring in pairs, tetrads, or groups.Gram-stain-positive and nonmotile. Non-spore-forming. Facultativelyanaerobic and catalase-negative. Growth in 6.5% NaCl. No growth at 10 or45° C. Negative bile-esculin reaction. Gas is not produced in MRS broth.Acid is produced from d-glucose and some other sugars.Pyrrolidonylarylamidase and leucine aminopeptidase are produced. Alaninephenylalanine proline arylamidase and urease are negative. Does notdeaminate arginine. Vancomycin-sensitive. Pyruvate is not utilized.Voges-Proskauer-negative. Cell-wall murein is based on L-lysine (typeLys-D-Asp). DNA G+C content (mol %): 40.5 (T_(m)). Type species:Dolosigranulum pigrum Aguirre, Morrison, Cookson, Gay and Collins 1994,370^(VP) (Aguirre, Morrison, Cookson, Gay and Collins 1993, 610.)

In another aspect, the Simonsiella species is characterized as follows:Proteobacteria/Betaproteobacteria/Neisseriales/Neisseriaceae/Simonsiella.Organisms that exist in characteristic multicellular filaments that areflat rather than cylindrical and often segmented into groups of eightcells. The width of an individual cell is greater than its length. Thelong axis of an individual cell is perpendicular to the long axis of thefilament. The diameter of the filaments (the width of the individualcells) may vary from about 2.0 to 8.0 μm, and the length of filamentsmay vary from about 10.0 to over 50.0 μm. Individual cells within thefilaments may be from about 0.5 to 1.3 μm long. In thin sections cutperpendicular to the long axis of the filament, the cells are flattenedand curved to yield a crescent-shaped, convex-concave (dorsal-ventral)asymmetry. The ends of the individual filaments are rounded. Gramnegative. Gliding motility of the entire filament in the direction ofthe long axis when the flat side of the filament is in contact with asurface. Chemoorganotrophs. Aerobic. Some may produce acid aerobicallyfrom carbohydrates. Optimal temperature: 37° C. Found in the oral cavityof warm-blooded vertebrates. The mol % G+C of the DNA is: 41-55. Typespecies: Simonsiella muelleri Schmid in Simons 1922, 504.

In yet other aspects, the Corynebacterium species is characterized asfollows:Actinobacteria/Actinobacteria/Corynebacteriales/Corynebacteriaceae/Corynebacterium.Straight to slightly curved rods with tapered ends. Rods are usuallyshort or of medium length. Club-shaped forms may be observed; sometimesellipsoidal, ovoid or rarely, “whip handles” (see below, Corynebacteriummatruchotii) or thinner rods with bulges (see below, Corynebacteriumsundsvallense) observed. Snapping division produces angular and palisadearrangements of cells. Gram-stain-positive; some cells stain unevenly.Metachromatic (synonym being polyphosphate) granules may be observed forsome species. Not-acid-fast (Ziehl-Neelsen stain), and no species hasaerial mycelium. Nonsporeforming. All species are nonmotile. All speciesare catalase positive. All species are oxidase negative except forCorynebacterium bovis, Corynebacterium aurimucosum, Corynebacteriumdoosanense, and Corynebacterium marls (below). Many species arefacultatively anaerobic and some are aerobic. Chemoorganotrophs. Somespecies are lipophilic. Many species produce acid from glucose and someother sugars in peptone media. Several species alkalinize citrate assole carbon sources, but most do not. DNA G+C content (mol %): 46-74.Type species: Corynebacterium diphtheriae (Kruse 1886) Lehmann andNeumann 1896, 350 (“Bacillus diphtheria” Kruse in Flügge 1886, 225).

In some embodiments, the Corynebacterium species is one or more of thefollowing species: C. accolens, C. afermentans, C. ammoniagenes, C.amycolatum, C. argentoratense, C. aquaticum, C. auris, C. bovis, C.diphtheria, C. equi (now Rhodococcus equi), C. efficiens, C. flavescens,C. glucuronolyticum, C. glutamicum, C. granulosum, C. haemolyticum, C.halofytica, C. kroppenstedtii, C. jeikeium (group JK), C. macginleyi, C.matruchotii, C. minutissimum, C. parvum (Propionibacterium acnes), C.paurometabolum, C. propinquum, C. pseudodiphtheriticum (C. hofmannii),C. pseudotuberculosis, C. ovis, C. pyogenes-Trueperella pyogenes, C.urealyticum (group D2), C. renale, C. spec, C. striatum, C. tenuis, C.ulcerans, C. urealyticum, and C. xerosis.

In certain aspects, the Simonsiella species, Corynebacterium species,and/or Dolosigranulum species are obtained from the oral cavity, nasalcavity, or anterior nares of warm-blooded vertebrates (e.g., humans).

Such pharmaceutical compositions may take any physical form necessarydepending on a number of factors including the desired method ofadministration. Such physical forms include a solid, liquid, sol, gel,aerosol, or any other physical form now known or yet to be disclosed.The concept of a pharmaceutical composition including at least oneprobiotic organism also encompasses the at least one probiotic organismwithout any other additive. The physical form of the invention mayaffect the route of administration and one skilled in the art would knowto choose a route of administration that takes into consideration boththe physical form of the at least one probiotic organism and the desiredresult (e.g., reduced colonization of the anterior nares and/or nasalcavity). Pharmaceutical compositions that include the at least oneprobiotic organism may be prepared using methodology well known in thepharmaceutical art. A pharmaceutical composition that includes the atleast one probiotic organism may include a second effective compound,such as an antibiotic compound (e.g., mupirocin).

Pharmaceutical compositions including the at least one probioticorganism include materials capable of modifying the physical form of adosage unit. In one nonlimiting example, the composition includes amaterial that forms a coating that holds and/or supports the at leastone probiotic organism. Materials that may be used in such a coatinginclude, for example, sugar, shellac, gelatin, or any other inertcoating agent.

Pharmaceutical compositions including the at least one probioticorganism may be prepared as an aerosol. Aerosols encompass a variety ofsystems including colloids and pressurized packages. Delivery of acomposition in this form may include propulsion of a pharmaceuticalcomposition including the at least one probiotic organism through use ofliquefied gas or other compressed gas or by a suitable pump system.Aerosols may be delivered in single phase, bi-phasic, or tri-phasicsystems.

Pharmaceutical compositions that include the at least one probioticorganism may also include a pharmaceutically acceptable carrier.Carriers include any substance that may be administered with the atleast one probiotic organism with the intended purpose of facilitating,assisting, or helping the administration or other delivery of the activepharmaceutical agent. Carriers include any liquid, solid, semisolid,gel, aerosol or anything else that may be combined with the activepharmaceutical agent to aid in its administration. Examples includediluents, adjuvants, excipients, water, oils (including petroleum,animal, vegetable or synthetic oils.) Such carriers include particulatessuch as a tablet or powder, liquids such as an oral syrup or injectableliquid, and inhalable aerosols. Further examples include saline, gumacacia, gelatin, starch paste, talc, keratin, colloidal silica, andurea. Such carriers may further include binders such as ethyl cellulose,carboxymethylcellulose, microcrystalline cellulose, or gelatin;excipients such as starch, lactose or dextrins; disintegrating agentssuch as alginic acid, sodium alginate, Primogel, and corn starch;lubricants such as magnesium stearate or Sterotex; glidants such ascolloidal silicon dioxide; sweetening agents such as sucrose orsaccharin, a flavoring agent such as peppermint, methyl salicylate ororange flavoring, or coloring agents. Further examples of carriersinclude polyethylene glycol, cyclodextrin, oils, or any other similarliquid carrier that may be formulated into a capsule. Still furtherexamples of carriers include sterile diluents such as water forinjection, saline solution, physiological saline, Ringer's solution,isotonic sodium chloride, fixed oils such as synthetic mono ordiglycerides, polyethylene glycols, glycerin, cyclodextrin, propyleneglycol or other solvents; antibacterial agents such as benzyl alcohol ormethyl paraben; antioxidants such as ascorbic acid or sodium bisulfite;chelating agents such as ethylenediaminetetraacetic acid; buffers suchas acetates, citrates or phosphates and agents for the adjustment oftonicity such as sodium chloride or dextrose, thickening agents,lubricating agents, and coloring agents. In some embodiments of theinvention, the pharmaceutically acceptable carrier can comprise a growthmedium that can support the growth and/or static existence of the atleast one probiotic organism in the context of the pharmaceuticalcomposition prior to administration of the pharmaceutical composition tothe subject. For example, the pharmaceutical composition can compriseone or pharmaceutically acceptable carrier to provide sufficientsustenance for the at least one probiotic organism that are alsocompatible with the desired route of administration (e.g., intranasaladministration).

The pharmaceutical composition including the active pharmaceutical agentmay take any of a number of formulations depending on thephysicochemical form of the composition and the type of administration.Such forms include solutions, suspensions, emulsions, tablets, pills,pellets, capsules, capsules including liquids, powders,sustained-release formulations, directed release formulations,lyophylates, suppositories, emulsions, aerosols, sprays, granules,powders, syrups, elixirs, or any other formulation now known or yet tobe disclosed. Additional examples of suitable pharmaceutical carriersare described in “Remington's Pharmaceutical Sciences” by E. W. Martin,hereby incorporated by reference in its entirety.

Methods of administration include, but are not limited to, oraladministration and parenteral administration. Parenteral administrationincludes, but is not limited to intradermal, intramuscular,intraperitoneal, intravenous, subcutaneous, intranasal, epidural,sublingual, intranasal, intracerebral, intraventricular, intrathecal,intravaginal, transdermal, rectal, by inhalation, or topically to theears, nose, eyes, or skin. Other methods of administration include butare not limited to infusion techniques including infusion or bolusinjection, by absorption through epithelial or mucocutaneous liningssuch as oral mucosa, rectal and intestinal mucosa. Compositions forparenteral administration may be enclosed in ampoule, a disposablesyringe or a multiple-dose vial made of glass, plastic or othermaterial.

The term “therapeutically effective amount” as used herein means thatthe amount/number of colony forming units of the at least one probioticorganism contained in the pharmaceutical composition administered thatis of sufficient quantity to achieve the intended purpose, such as, inthis case, to control, treat, reduce, eliminate, and/or prevent thecolonization of the subject by a potentially pathogenic microorganism,such as S. aureus. The addition of a therapeutically effective amount ofthe pharmaceutical composition encompasses any method of dosing of acomposition. Dosing of the at least one probiotic organism may includesingle or multiple administrations of any of a number of pharmaceuticalcompositions that include the at least one probiotic organism as anactive ingredient. Examples include a single administration, a course oftreatment involving several treatments on a regular or irregular basis,multiple administrations for a period of time until a diminution ofcolonization is achieved, preventative treatments applied prior to theinstigation of colonization, or any other dosing regimen known in theart or yet to be disclosed that one skilled in the art would recognizeas a potentially effective regimen. A final dosing regimen including theregularity of and mode of administration will be dependent on any of anumber of factors including but not limited to the subject beingtreated; the severity of the affliction; the manner of administration,the stage of colonization, the presence of one or more other conditionssuch as pregnancy, infancy, or the presence of one or more additionaldiseases; or any other factor now known or yet to be disclosed thataffects the choice of the mode of administration, the dose to beadministered and the time period over which the dose is administered.

Examples

The familiarity with the exterior of the nose belies the intriguingpuzzle within. Individuals can have distinctive susceptibilities tonasal colonization by Staphylococcus aureus, a major pathogen (1); yet,it also appears that host genetics is not a significant determinant ofS. aureus nasal colonization (2). One potential explanation for thisdissonance is that individuals' susceptibility to S. aureus nasalcolonization is driven by an environmentally determined phenotype. Tosatisfy this explanation, the phenotype should have limited associationwith host genetics, but it should predict S. aureus nasal colonization.As the human microbiome is increasingly considered a host phenotype(3-5), the investigators examined the potential role of nasal microbiotain S. aureus nasal colonization. Testing this hypothesis provided usefulinsight into the malleability of nasal microbiota and explanations forprevious contradictory findings regarding S. aureus' negativeassociation with nasal bacteria such as Propionibacterium andStaphylococcus epidermidis (6-10).

To test this hypothesis, the investigators enrolled and collected nasalswabs from 46 monozygotic and 43 dizygotic twin pairs (Table 1), whichwere cultured for S. aureus using standard non-selective media aspreviously described (2). The investigators measured nasal bacterialdensity (i.e., the amount of nasal bacteria present) using abroad-coverage quantitative PCR (11) and characterized nasal microbiotacomposition (i.e., the types and proportions of bacteria present in thenasal microbiota) by 16S rRNA gene-based sequencing and taxonomicclassification, as previously described (12), with some modifications.Using the taxonomically-classified sequence data, the investigatorscalculated the proportional abundance for each nasal bacterial taxon as:(Number of sequences assigned to the taxon from the sample)/(Totalnumber of sequences from the sample), which the investigators combinedwith nasal bacterial density to calculate taxon absolute abundance as:(Proportional abundance of the taxon from the sample)×(nasal bacterialdensity of the sample) (12).

TABLE 1 *Atopic diseases include asthma, atopic dermatitis, and allergy.Dizygotic Monozygotic Same Sex Opposite Sex (n = 46 pairs) (n = 23pairs) (n = 20 pairs) Number of individuals or twin pairs (%) Age 50-54yr 12 (26.1) 0 (0.0) 0 (0.0) 55-59 yr 13 (28.3) 0 (0.0) 0 (0.0) 60-64 yr7 (15.2) 4 (17.4) 1 (5.0) 65-69 yr 9 (19.6) 4 (17.4) 11 (55.0) 70-74 yr3 (6.5) 12 (52.2) 7 (35.0) 75-79 yr 2 (4.4) 3 (13.0) 1 (5.0) Sex Female25 (54.4) 16 (69.6) 20 (100.0) Male 21 (45.6) 7 (30.4) Smoking Smoker 14(15.2) 9 (19.6) 10 (25.0) Concordance 40 (87.0) 16 (69.6) 12 (60.0)History of Atopic Disease* Yes 27 (29.3) 14 (30.4) 13 (32.5) Concordance31 (86.1) 15 (65.2) 15 (75.0) History of Psoriasis Yes 8 (9.7) 2 (4.3) 5(12.5) Unknown 1 (2.2) 1 (4.3) 2 (2.5) Concordance 39 (84.8) 20 (87.0)14 (70.0) Farm Exposure Yes 1 (1.1) 2 (4.3) 1 (2.5) Unknown 0 (0.0) 2(8.7) 0 (0.0) Concordance 45 (97.8) 21 (91.3) 19 (95.0)

The nasal bacterial density and microbiota composition were highlydiverse among the 178 healthy, community-dwelling middle-aged adults.The median nasal bacterial density was 4.4×10⁶ 16S rRNA gene copies perswab, and it spanned nearly four orders of magnitude, from 6.7×10⁵ to2.1×10⁹ 16S rRNA gene copies per swab (Inter-Quartile Range (IQR):1.6×10⁶-1.7×10⁷). Many bacteria were found in large proportions ofsubjects, such as Corynebacterium (n=157/178, 88.2%), Propionibacteriumacnes (n=149/178, 83.7%), Staphylococcus epidermidis (n=161/178, 90.4%),but proportional abundance varied substantially across individuals,contributing to distinctive microbiota compositions. The investigatorsidentified seven major nasal community state types (CST1-7) among ourparticipants (FIGS. 1A-C). Each CST had uniquely high prevalence andproportional abundance of specific nasal bacteria, as identified byindicator analysis: S. aureus defined CST1, Enterobacteriaceae—includingEscherichia spp., Proteus spp., and Klebsiella spp.—defined CST2,Staphylococcus epidermidis defined CST3, Proprionibacterium spp. definedCST4, Corynebacterium spp. defined CST5, Moraxella spp. defined CST6,and Dolosigranulum spp. defined CST7 (Table 2). The most prevalent nasalCST was CST4 (n=51/178, 28.7%), followed by CST3 (n=40/178, 22.5%) andCST1 (n=22/178, 12.4%). CST6 was the least common, with only 5.6%prevalence (n=10/178) (Table 3). Thus, this study revealed distinctivenasal CSTs and greater nasal microbiota heterogeneity than previouslyreported (6-10), particularly among Enterobacteriaceae, of which Proteusand Serratia were not previously known to dominate the nasal microbiota.

TABLE 2 *FDR-adjusted: adjusted by false-discovery rate AverageProportional FDR- Abundance Indicator Unadjusted adjusted* CST IndicatorTaxa (SD) Value p-value p-value 1 Staphylococcus aureus 0.38 (0.13) 0.821.00E−04 3.57E−04 Staphylococcus aureus CI < 0.8 0.31 (0.10) 0.801.00E−04 3.57E−04 Staphylococcus auricularis CI < 0.8 0.06 (0.04) 0.841.00E−04 3.57E−04 Staphylococcus lugdunensis CI < 0.8 0.01 (0.01) 0.423.00E−04 8.82E−04 2 Escherichia unclassified 0.29 (0.44) 0.46 3.00E−048.82E−04 Enterobacteriaceae unclassified CI < 0.8 0.15 (0.27) 0.377.00E−04 1.84E−03 Klebsiella CI < 0.8 0.04 (0.08) 0.43 1.80E−03 4.29E−03Proteus vulgaris CI < 10.8 0.03 (0.07) 0.23 2.70E−03 5.87E−03 Proteusvulgaris 0.09 (0.22) 0.19 5.90E−03 1.23E−02 Raoultella CI < 0.8 0.04(0.10) 0.17 2.65E−02 4.88E−02 Erwinia CI < 0.8 0.08 (0.16) 0.30 3.55E−025.92E−02 Averyella CI < 0.8 0.06 (0.16) 0.12 4.24E−02 6.84E−02 3Staphylococcus epidermidis 0.26 (0.11) 0.50 1.00E−04 3.57E−04Staphylococcus capitis CI < 0.8 0.02 (0.01) 0.43 1.00E−04 3.57E−04Staphylococcus caprae CI < 0.8 0.01 (0.01) 0.41 1.00E−04 3.57E−04Staphylococcus epidermidis CI < 0.8 0.14 (0.06) 0.49 1.00E−04 3.57E−04Staphylococcus pettenkoferi CI < 0.8 0.005 (0.004) 0.41 1.00E−043.57E−04 Staphylococcus warneri CI < 0.8 0.03 (0.02) 0.44 1.00E−043.57E−04 Staphylococcus hominis CI < 0.8 0.02 (0.02) 0.44 3.00E−048.82E−04 Staphylococcus pasteuri CI < 0.8 0.01 (0.01) 0.35 5.00E−041.39E−03 Anaerococcus unclassified 0.01 (0.01) 0.25 1.76E−02 3.52E−02Stenotrophomonas unclassified 0.05 (0.07) 0.24 2.04E−02 3.92E−02Staphylococcus haemolyticus CI < 0.8 0.01 (0.01) 0.28 2.73E−02 4.88E−024 Propionibacterium acnes 0.12 (0.15) 0.35 2.70E−03 5.87E−03 5Corynebacteriaceae unclassified 0.01 (0.02) 0.25 3.48E−02 5.92E−02Corynebacterium tuberculostearicum 0.01 (0.01) 0.52 1.00E−04 3.57E−04Corynebacterium unclassified 0.54 (0.12) 0.51 1.00E−04 3.57E−04Corynebacterium unclassified CI < 0.8 0.10 (0.04) 0.48 1.00E−04 3.57E−04Corynebacterium tuberculostearicum CI < 0.8 0.02 (0.01) 0.32 1.30E−033.25E−03 6 Moraxella unclassified 0.55 (0.10) 0.81 1.00E−04 3.57E−04 7Dolosigranulum unclassified 0.41 (0.20) 0.56 1.00E−04 3.57E−04

TABLE 3 *Comparison of nasal CST distribution in men versus womenresulted in χ2 = 7.8, df = 6, p = 0.25 Sex* Nasal bacterial densityFemale Male Total Median Q1-Q3 (n = 102) (n = 76) (n = 178) 16S rRNAgene copies per swab Number (%) CST1 5.33E+06 4.01E+06-9.39E+06 16(15.7)  6 (7.9) 22 CST2 4.10E+07 2.03E+07-3.88E+08 10 (9.8)  6 (7.9) 16CST3 2.06E+06 1.49E+06-5.28E+06 25 (24.5) 15 (19.7) 40 CST4 2.22E+061.10E+06-1.81E+08 27 (26.4) 24 (31.5) 51 CST5 4.81E+06 2.00E+06-1.46E+07 9 (8.8) 11 (14.5) 20 CST6 1.37E+07 2.46E+06-1.78E+07  4 (3.9)  6 (7.9)10 CST7 5.15E+06 2.13E+06-1.24E+07 11 (10.8)  8 (10.5) 19

Was Nasal Microbiota Significantly Associated with Host Genetics?

Host genetics played no significant role in nasal microbiotacomposition. Among monozygotic twin pairs, only 26.1% had the same nasalCSTs (n=12/46) (FIG. 1C), which was comparable to the 25.6% amongdizygotic twin pairs (n=11/43) (FIG. 2A-2C). The investigators confirmedthe limited similarity in nasal microbiota composition of monozygotictwin pairs by ecological distance-based analysis, where we found thatnasal microbiota of monozygotic twins were not more similar than all orsame-sex dizygotic twins, or than unrelated same-sex pairs (Table 4).

TABLE 4 MZ versus randomly-selected, same MZ versus DZ sex non-twinpairs Female Male Female Male Overall Jaccard's Mean −0.037 0.109 −0.064−0.041 −0.049  2.5% CL −0.15 −0.047 −0.178 −0.131 −0.122 97.5% CL 0.070.251 0.047 0.063 0.022 Bray-Curtis Mean −0.033 0.109 −0.076 −0.061−0.063  2.5% CL −0.166 −0.082 −0.216 −0.182 −0.154 97.5% CL 0.112 0.2790.055 0.057 0.026 Euclidean Mean −130257 94896 −50014 −26934 −32343 2.5% CL −388536 13490 −221823 −169013 −145271 97.5% CL 76979 23508695268 118081 78943

In contrast, host genetics and nasal bacterial density weresignificantly linked. Nasal bacterial densities of monozygotic twinpairs were significantly more correlated than dizygotic twin pairs (Sex-and age-adjusted Intra-class Correlation Coefficient (ICC) in MZ twins:0.42, 95% Cl: 0.12-0.65 and for DZ twins: −0.06, 95% CI −0.35-0.23). Thevariations in nasal bacterial density were best explained by a modelthat comprised additive genetic and non-shared environmental effects(Table 5). Approximately 30% of the variation in nasal bacterial densitywas heritable (95% Cl: 6%-54%) with a large non-shared environmentaleffect of 70% (95% Cl: 46%-94%).

The sex of the host also significantly influenced nasal bacterialdensity. On average, nasal bacterial density of women was approximatelyhalf that of men (Women Median: 2.97×10⁶ 16S rRNA gene copies per swab,IQR: 1.33×10⁶-9.11×10⁶; Men Median: 7.94×10⁶, IQR: 2.20×10⁶-4.30×10⁷)(Wilcoxon rank-sum p<0.001) (FIG. 3A, Table 6). Smoking and the historyof atopic diseases or psoriasis had no significant effect on nasalbacterial density (Smoking p=0.61, Psoriasis p=0.22, Psoriasis p=0.22)(Table 6).

The types of nasal bacteria present were also associated with nasalbacterial density, as indicated by the significantly different densitiesacross CSTs (ANOVA p<0.001). Bacterial density was highest in the twoleast prevalent CSTs: Enterobacteriaceae-dominated CST2 andMoraxella-dominated CST6; in contrast, bacterial densities were lowestin the two most prevalent CSTs: CST3 and CST4 (Table 3). The distinctivedensities across nasal CSTs indicate that density may be a uniquefeature of the individual nasal CSTs.

The sex difference in nasal bacterial densities was not due to men'spropensity for high-density nasal CSTs. The investigators found nosignificant sex difference in nasal CST distribution (χ2=7.8, df=6,p=0.25) (Table 3). Overall, men had higher nasal bacterial density thanwomen, irrespective of nasal CSTs (p<0.001) (Table 7).

TABLE 5 Correlation Correlation log P- Models within MZ within DZ A (%)D (%) C (%) E (%) likelihood value* AIC U** 0.42  −0.06 0 0 0 0 −205.7423.4 (0.12, 0.65) (−0.35, 0.23)   ACE 0.30* 0.15 30 0 0 70 −207.2 426.5(0.05, 0.51) (0.03, 0.27) (6, 54) (−, −) (46, 94) ADE 0.38  0.1 0 38 061.9 424.8 (0.13, 0.59) (0.04, 0.15) (−, −) (15.62) 0 (38, 85) −206.4AE^(§) 0.30* 0.15 30 0 0 70 −207.2 0.19 424.5 (0.05, 0.51) (0.03, 0.27)(6, 54) (46, 94) E 0 0 0 1 −209.3 0.04 426.6 *P-value from comparingforcing correlation of MZ to be twice the correlation of DZ in thepolygenetic model. The AE model was compared to ADE model and the Emodel was compared to the AE model. **U model is a model with equalregression, intercept, and residual variance for twin 1 and twin 2 aswell as for MZ and DZ twins ^(§)The AE model was selected as the finalmodel.

Can the Nasal Microbiota Predict S. aureus Nasal Colonization?

The rates and absolute abundance of S. aureus differed among nasal CSTs(FIG. 4A-B). Some taxa predict the presence/absence of S. aureus, whileothers predict S. aureus absolute abundance in a threshold-dependentfashion (FIG. 3A). Dolosigranulum spp. was the most informativepredictor of S. aureus presence/absence. Specifically, the rate of S.aureus nasal colonization among individuals at or above theDolosigranulum threshold was 16.0% (n=4/25), as compared with 56.0%among the simulated population (n=56/100). Likewise, the investigatorsobserved threshold effects for nasal taxa such as Propionibacteriumgranululosum and S. epidermidis; however, P. granululosum was negativelycorrelated with the presence of S. aureus, but S. epidermidis waspositively correlated (P. granululosum node n=4/34, 11.8%; S.epidermidis node n=13/14, 92.9%) (FIG. 5A).

The S. aureus absolute abundance model indicated that having lowCorynebacterium abundance predicts high S. aureus absolute abundance,i.e., Category 5, which comprised 10⁶-10⁷ S. aureus 16S rRNA gene copiesper swab (14/28, 50.0%) (FIG. 6A), as compared to the lower Category 5prevalence in the simulated population (n=16/100, 16.0%) (FIG. 6B).Results from validation tests recapitulated and supported thethreshold-dependent relationships between S. aureus and other nasal taxafrom both models (FIG. 5B, FIG. 6C). Thus, these findings indicate thatnasal taxa determine S. aureus nasal colonization through two types ofinteractions: by exclusion and by limiting S. aureus abundance.Ecologically, these relationships may manifest as a result ofcompetition or common sorting along an abiotic axis.

Culture-Negative S. aureus Nasal Colonization.

In the current study, men and women did not differ in S. aureus nasalcolonization rates by DNA sequencing (Women 52.9%; Men 52.6%). Thiscontradicted previous culture-based studies that have showed men aremore likely to be colonized by S. aureus (2, 13-15). However, thisdiscrepancy could be explained by the higher absolute abundance of S.aureus in men and its influence on culture outcomes. Specifically,except in CST1, women frequently had 10- to 100-fold lower S. aureusabsolute abundance than men (FIG. 3B). At the same time, S. aureusabsolute abundance had a strong positive link to culture outcome. Each10-fold increase in S. aureus increased the probability of a positiveculture by 30.0% (r²=0.33, p<0.001) (FIG. 3C). After adjusting for sexand other host factors, S. aureus absolute abundance was the keydeterminant of culture-positive S. aureus nasal colonization (r²=0.33,p<0.05). This suggests that culture-based methods fail to identify asubstantial proportion of S. aureus carriers, particularly among women,which could serve as unrecognized reservoirs of S. aureus (13).

In summary, nasal microbiota is an environmentally derived hostphenotype and nasal taxa determine S. aureus nasal colonization byinfluencing S. aureus presence/absence and absolute abundance. Nasalmicrobiota composition is not fixed by host genetics and is thereforesusceptible to environmental modification. These findings open thepossibility for probiotic strategies to eliminate S. aureus nasalcolonization. One caveat here is the significant influence of sex andhost genetics on nasal bacterial density. In addition, even though earlyenvironment had no significant influence in our cohort, which was middleage or older, it could play a role in a younger cohort. In this study,absolute abundance emerged as a critical factor in nasal bacterialinteractions and culture-based detection. In particular, the negativeinteractions between nasal taxa and S. aureus depended on absoluteabundance thresholds, consistent with the ecological notion thatabsolute abundances, not relative abundances, reveal the importance ofecological interactions such as competition (16, 17). Thus, the utilityof nasal probiotics will rely on whether nasal microbiota compositiontrumps nasal bacterial density in determining S. aureus nasalcolonization. Based on the limited influence of host genetics on S.aureus nasal colonization (2), we predict that the answer will be “yes”.

Laboratory Methods

A. DNA isolation and purification. All samples from each subject wereprocessed in the same batch to control for inter-run variation in lysisand purification. The combined chemical and mechanical lysis wasperformed as follows: Swab samples were thawed at 4° C. and 100 μl ofswab eluent from each sample was transferred to pre-labeled PCTMicroTube (Pressure Bioscience, Inc., South Easton, Mass., USA)containing 50 μl of RLT lysis buffer (Qiagen, Valencia, Calif., USA) andcapped with a 150 μl PCT MicroCap (Pressure Bioscience, Inc.). Eachcapped MicroTube was loaded onto the MicroTube holder and undergomechanical lysis on the Barocycler NEP 3229 instrument (PressureBioscience, Inc.) using the following pressure cycling conditions at 25°C.: increase pressure to 35,000 pounds per square inch (psi) for 15seconds, then decrease to 14.696 psi for 15 seconds and repeat for 19more cycles. The lysate was added to 550 μl of RLT lysis buffer andpurified using the AllPrep DNA/RNA Mini Kit following manufacturer'sinstructions. DNA elution was performed with 100 μl of Buffer EB. Thepurified DNA was used in subsequent qPCR and pyrosequencing analysis.

B. 16S rRNA gene-based broad-coverage qPCR. Each 16S qPCR reaction wasperformed in 10 μl reaction volumes in PRISM™ 384-well Clear OpticalReaction Plates (Applied Biosystems by Life Technologies, Grand Island,N.Y., USA) using methods as described previously. An in-run standardcurve spanning 10²-10⁸ in serial 10-fold dilutions was included in allruns and all samples were analyzed in triplicate reactions. Rawexperimental data, including the cycle threshold (Ct) and gene copynumber values for each reaction were exported from the SequenceDetection Systems v2.3 software (Applied Biosystems) using a manual Ctthreshold of 0.05 and automatic baseline. The Ct standard deviation foreach sample was further processed, where samples with Ct standarddeviation ≥0.25 were examined for outliers, defined as a singlereplicate with Ct-value that is ≥0.25 away from the remaining tworeplicates, which were then removed. The processed data was then used tocalculate the finalized Ct-value, as well as the 16S rRNA gene copynumber by plotting the Ct-value against linear regression of the in-runstandard curve.

C. Generation of 16S rRNA gene V3V6 amplicons. Amplification of the V3V6region of the 16S rRNA genes in each DNA sample was performed in a96-well format using 50 μl reactions and thermocycling conditions aspreviously described. In each optimized 50 μl reaction, 10 μl of DNA wasadded to 40 μl of PCR reaction mix with a final concentration of 400 nMof each broad range fusion forward primer(5′-CCATCTCATCCCTGCGTGTCTCCGA-CTCAGnnnnnnnn CCTACGGGDGGCWGCA-3′ (SEQ IDNO: 1)) and fusion reverse primer(5′-CCTATCCCCTGTGTGCCTTGGCAGTCTCAGCTGACGACRRCCRTGCA-3′ (SEQ ID NO: 2)),with the underlined portion denoting FLX Lib-L adapter sequence,italicized portion denoting the sample-specific 8-nt barcode sequence,and bolded portion denoting 16S rRNA gene primer sequence, 10×PCR bufferwithout MgCl₂ (Invitrogen), 2.5 mM MgCl₂, 0.5 mM dNTP mix, 0.067 U/μlPlatinum® Taq DNA Polymerase (Invitrogen), and molecular grade H₂O usingthe following thermocycling condition: 90 seconds at 95° C. for initialdenaturation and UNG inactivation, 30 seconds at 95° C. fordenaturation, 30 seconds at 62° C. for annealing, 30 seconds at 72° C.for extension, with the annealing temperature decreasing by 0.3° C. foreach subsequent cycle for 19 cycles, followed by 10 cycles ofamplification consisting of 30 seconds at 95° C. for denaturation, 30seconds at 45° C. for annealing, 30 seconds at 72° C. for extension, anda final extension for 7 minutes at 72° C. and cool down to 15° C. PCRproducts were frozen immediately at −20° C. until further processing. Ineach fusion PCR experiment, negative and positive extraction controlswere included, as well as PCR controls including a no-template control,a positive bacterial control (E. coli genomic DNA at 1 pg/μl), and ahuman DNA control (human genomic DNA at 10 ng/μl). The resultant fusionPCR product were analyzed using 1% E-Gel® 96 Agarose (Invitrogen) toconfirm PCR amplification and product band size. The barcoded 16S rRNAgene amplicons from each sample underwent 4 ten-fold dilutions and werequantified using the 16S rRNA gene-based broad-coverage qPCR describedearlier. The resultant barcoded amplicons were pooled in an equimolarfashion. The pooled barcoded 16S rRNA gene amplicon library underwentemulsion PCR, bead enrichment and recovery, and pyrosequencing analysison the Genome Sequencer FLX instrument (454 Life Sciences, Branford,Conn., USA).

Bioinformatics Methodological Details

A. Chimeric sequence removal. The investigators first converted thestandard flowgram format (SFF) files into fasta sequence and qualityfiles using a combination of in-house Perl-based wrappers and the 454Sequencing System Software 1. Next, the investigators identifiedchimeric sequences de novo using U-Search's cluster utility (U-Searchversion 5.0⋅144) and U-Chime at the 99% threshold. Only non-chimericsequences were included in subsequent analysis.

B. Sequence barcode removal, binning, and quality filtering. Theinvestigators next assigned each pyrosequence to its original sample andscanned for primer sequence using a QIIME utility. Pyrosequences withoutvalid barcode or primer were excluded. The investigators filtered thedemultiplexed pyrosequences based on: a) length (150 bp-920 bp), b)number of degenerate bases (a maximum of six), c) mean quality score (alower threshold of 25), and d) homopolymer length (a maximum consecutiverun of six). Lastly, the investigators trimmed each sequence based onquality using a sliding window of 50 bp and a quality score threshold of25.

C. Taxonomic Classification. The resultant demultiplexed andquality-checked 16S rRNA gene sequences were classified at eachtaxonomic level (i.e., phylum, class, order, family, genus) at ≥80%bootstrap confidence level using a web service for the Naïve BayesianClassifier (RDP Release 10, Update 28). Sequences classified at <80%bootstrap confidence level are reported with the assigned taxon and a“Cl<0.80” notation. The taxonomic classifications assigned to thesequences through the RDP Classifier fall into the modern high-orderbacterial proposed by Garrity et. al. A total of 327,716 bacterial 16SrRNA gene sequences were obtained and classified. Classification resultsfor each sample are enumerated to generate an abundance-based matrix fordata analysis. Bacterial taxa that comprised 0.2% of total sequenceswere included in subsequent analysis.

D. Species classifier development and validation. The Naïve-Bayesian RDPClassifier is one of the current gold standards for high-throughputclassification of bacteria I6S rRNA gene sequences; however, at thistime, it does not provide species level classification, which limits ourability to examine Staphylococcus and of other nasal taxa at thespecies-level, if sufficient resolution exists. In order to achievethis, we re-built the RDP Classifier with an external taxonomy andcurated sequences, with the particular goal of improving Staphylococcusspecies resolution because it is of major ecological importance in thenasal cavity.

Thus, the investigators developed a pipeline that will read an externaltaxonomy, create a database to maintain the taxonomic information, buildtraining files from the database solution, re-train the RDP Classifier,and generate classifications for a set of query sequences. The generalworkflow is depicted below:

D1. Training set curation. Fundamental to the entire process mentionedabove is the acquisition of a training set, which can be used as a modelfor generating taxonomic classifications. Staphylococcus sequences thatare missing or underrepresented in our training set may be assignedincorrectly or with low confidence level. Greengenes and RDPStaphylococcus sequences were used as the core of our training set andcuration is ongoing.

D1a. Greengenes. The majority of the training set is comprised ofsequences from the Greengenes taxonomy. While trying to build rawtraining files (described in the section titled “Creating Raw TrainingFiles”), it became apparent that polyphyletic groups exist in thecurrent Greengenes taxonomy. Re-training the RDP Classifier was notpossible until these groups were either resolved, or removed from thetaxonomy. The approach to overcoming this obstacle was to insert thepolyphyletic taxonomy into a database, and then build training filesfrom the database solution such that a given sequence's membership in apolyphyletic group is clearly indicated.

A taxon is considered polyphyletic if it has more than one parent.Consider the two lineage strings below:

182310

Root;k_Bacteria;p_Proteobacteria;c_Gammaproteobacteria;o_Alteromonadales;f_Alteromonadaceae;g_Alteromonas:s_Alteromonasmarina

250345

Root;k_Bacteria;p_Proteobacteria;c_Gammaproteobacteria:o_Oceanospirillales;f_Alteromonadaceae;g_Marinobacter:s_

The family Alteromonadaceae is polyphyletic because it has two parents.Our solution generates training files that indicate this relationship inthe manner demonstrated below:

182310

Root; k_Bacteria;p_Proteobacteria;c_Gammaproteobacteria;o_KNOWN_POLYPHYLETIC_GROUP[Alteromonadales,Oceanospirillales];f_Alteromonadaceae;

D1b. Ribosomal Database Project. A set of training sequences was alsoacquired from the RDP project. This set is comprised of solely of typestrains assigned to the genus Staphylococcus to increase the confidenceof species-level assignment. The RDP sequence set underwent chimeracheck using UCHIME.

D2. Database Design. To facilitate efficient maintenance of and accessto the taxonomy, a relational database solution was implemented. Inorder to optimize efficient querying of the database, reduce spaceconsumption, and to eliminate redundant entries within the database, atable for each rank was implemented; the consequence of this is that itis only necessary to insert a specific taxon once. Synonym tables wereadded to facilitate querying of the database in a manner that allowedmembership in a polyphyletic group to be reflected in the resultingtraining files. The database design is provided in the diagram attachedwith this document:

To insert sequences into the database, the insert_taxonomy.py isutilized:

-   -   python insert_taxonomy.py    -   -t taxonomy_file.txt    -   -o parsed_taxonomy_file.txt    -   -s RDP    -   -b yes    -   -a localhost    -   -m 16S_TAXONOMY_RDP_STAPH    -   -u root    -   -p password    -   -c create_all_tables.sql        -   -f seqs.fasta

Argument Explanation:

-   -   * -t The taxonomy file containing all the lineage strings    -   * -o The name of the parsed taxonomy file that will be generated    -   * -s Source of the taxonomy    -   * -b Flag to indicate whether a new database build is to be used        (values of y or yes will indicate to do so)    -   * -a Database host    -   * -m Database name    -   * -u Username    -   * -p Password    -   * -c Optional argument indicating the script for creating the        database tables    -   * -t Optional argument indicating the taxonomy dictionary that        will be used as a schema to build the database from    -   * -f The fasta file containing the sequences in the taxonomy

D3. Creating Training Files. The build_taxonomy.py script is used togenerate training files from the database. Usage is as follows:

-   -   python/PATH/build_taxonomy.py    -   -t yes    -   -o/PATH/training_rdp_download_1258seqs.txt    -   -a localhost    -   -d 16S_TAXONOMY_RDP_STAPH    -   -u root    -   -p password

Argument Explanation:

-   -   * -t Optional argument that indicates whether or not a training        file is to be generated. Any value will indicate yes.    -   * -o Output file    -   * -s Optional argument that indicates the source of the        taxonomy. This is only used if an original taxonomy file is to        be generated.    -   * -a Hostname    -   * -d Database name    -   * -u Username    -   * -p Password

The RDP Classifier training requires two raw training files as inputs: ataxonomy tree file containing the hierarchical taxonomy information, anda sequence file with lineage strings included in the headers. Both ofthese files are created with the create_raw_training_files.py script,which performs the following steps: 1. Modify/parse the taxonomy, 2.Modify/parse the sequence file, 3. Create the raw taxonomy tree file,and 4. Generate the updated sequence file. In order to run this script,the following command must be executed:

-   -   python create_raw_training_files.py    -   <taxonomy_file>    -   <sequence_file>    -   <output_raw_taxonomy_file>    -   <output_raw_seq_file>

Argument Explanation:

-   -   * <taxonomy_file>—The file generated by build_taxonomy.py        containing sequence ids and associated lineage strings    -   * <sequence_file>—The fasta file generated by build_taxonomy.py        containing all the training sequences    -   * <output_raw_taxonomy_file>—Output file containing hierarchical        taxonomy tree    -   * <output_raw_seq_file>—Output sequence file with lineage        included in the headers

D4. Modifying the Taxonomy. A hierarchical taxonomy tree file will begenerated as the output; however, for the tree to be valid, certainmodifications to the taxonomy must be made. It is a strict requirementthat all sequences in the taxonomy must not only have names for allranks, but they must also all be classified down to the same level.Consider the sequence 152262, which has a lineage of:

-   -   k_Bacteria;p_Chlamydiae;c_Chlamydiae;o_Chlamydiales;f_;g_    -   Our script will parse this lineage string such that the        following, valid string is generated:    -   k_Bacteria;p_Chlamydiae;c_Chlamydiae;o_Chlamydiales;f_Bacteria.Chlamydiae.Chlamydiae.Chlamydiales.unclassified_family;    -   g_Bacteria.Chlamydiae.Chlamydiae.Chlamydiales.Bacteria.Chlamydiae.Chlamydiae.Chlamydiales.unclassified_family.unclassified_genus;    -   s_Bacteria.Chlamydiae.Chlamydiae.Chlamydiales.Bacteria.Chlamydiae.Chlamydiae.Chlamydiales.unclassified_family.Bacteria.Chlamydiae.Chlamydiae.Chlamydiales.Bacteria.Chlamydiae.Chlamydiae.Chlamydiale        s.unclassified_family.unclassified_genus.unclassified_species

D5. Modifying the Sequence File. All sequences in the representativesequence file are modified such that they are in the format:

-   -   domain;phylum;class;order;family;genus;species

D6. The Taxonomy Tree File

create_raw_training_files.py modifies the taxonomy, and then generatesthe hierarchical taxonomy tree file from the revised taxonomy. Theformat for the taxonomy tree is depicted below:

-   -   taxid*taxon name*parent taxid*depth*rank

taxid, the parent taxid, and depth should be in integer format. depthindicates the depth from the root taxon. An example tree is given below:

-   -   1*Bacteria*0*0*domain    -   765*Firmicutes*1*1*phylum    -   766*Clostridia*765*2*class    -   767*Clostridiales*766*3*order    -   768*Clostridiaceae*767*4*family    -   769*Clostridium*768*5*genus    -   160*Proteobacteria*1*1*phylum    -   433*Gammaproteobacteria*160*2*class    -   586*Vibrionales*433*3*order    -   587*Vibrionaceae*586*4*family    -   588*Vibrio*587*5*genus    -   592*Photobacterium*587*5*genus    -   552*Pseudomonadales*433*3*order    -   553*Pseudomonadaceae*552*4*family    -   554*Pseudomonas*553*5*genus    -   604*Enterobacteriales*433*3*order    -   605*Enterobacteriaceae*604*4*family    -   617*Enterobacter*605*5*genus    -   161*Alphaproteobacteria*160*2*class    -   260*Rhizobiales*161*3*order    -   261*Rhizobiaceae*260*4*family    -   262*Rhizobium*261*5*genus

D7. Re-training the RDP Classifier. To re-train the classifier, it isnecessary to create parsed training files from the raw training data.Assuming the two raw files are created in mydir/mydata: mytaxon.txt andmytrainseq.fasta, the user will need to run the command to create parsedtraining files:

-   -   mkdir/PATH/mydata/mydata_trained        -   java -Xmx1g            -   -cp/PATH/rdp_classifier-version.jar                edu.msu.cme.rdp.classifier.train.ClassifierTraineeMaker    -   /PATH/mydata/mytaxon.txt    -   /PATH/mydata/mytrainseq.fasta        -   1        -   version1        -   test        -   /PATH/mydata/mydata_trained

Argument Explanation:

-   -   * <mydata/mytaxon.txt> Contains the hierarchical taxonomy        information    -   * <mydata/mytrainseq.fasta> Contains the raw training sequences    -   * <1> The trainset_no to mark the training files generated    -   * <version1> Holds the modification information of the taxonomy    -   * <mydata_trained> Specifies the output directory

Four parsed training files will be created and saved into directorymydata_trained:

-   -   * bergeyTrainingTree.xml    -   * genus_wordConditionalProbList.txt    -   * logWordPrior.txt    -   * wordConditionalProblndexArr.txt

After this is accomplished, the rRNAClassifier.properties file (foundwith the RDP source code) needs to be copied into the directorycontaining the files mentioned above. Effectively, these files willserve as the model from which classifications will be generated.

D8. Generating Classifications. To classify sequences, the user caneither choose to execute the RDP Classifier source code by itself, or touse the species_classification_generatorpy script. To execute the RDPSource Code, the user will need to execute the following command:

-   -   java -Xmx1g -jar/PATH/rdp_classifier-version.jar        -   -t/PATH/mydata/rRNAClassifier.properties        -   -q/PATH/sampledata/testQuerySeq.fasta        -   -o/PATH/testquery.out

Argument Explanation:

-   -   * -jar The RDP jar file to use    -   * -t The rRNAClassifier.properties file    -   * -q Query sequence file    -   * -o Output file

NOTE: If the -t option is not used, the classifier will use the standardtraining set, and species-level classifications will not be generated.The species_classification_generator.py script does more than justproduce the classifications. It parses headers of the .fna filesproduced by our current version of the pyro sequencing pipeline, runsthe RDP Classifier on the sequences contained in the .fna files, parsesthe output, upload the classification results into a database, andgenerates the .xls files. To run this script the user will need toexecute the following command:

-   -   python species_classification_generatorpy    -   -d seqs/    -   -r 090712_omoss_test    -   -s localhost    -   -m PYRO_SEQ_CLASSIFICATIONS    -   -u root    -   -p password    -   -j/PATH/rdp_classifier-2.4.jar    -   -c/PATH/ClassificationReporter.jar    -   -t/PATH/rRNACIassifierproperties

Argument Explanation:

-   -   * -d Data directory containing the sequences to be classified    -   * -r The name of the run that will be used to identify the        database tables containing the results of the classification    -   * -s MySQL hostname    -   * -m MySQL database to hold classifications    -   * -u MySQL username    -   * -p User password    -   * -j Path to the RDP Classifier jar file    -   * -c Path to the ClassificationReporter.jar file    -   * -t Path to the rRNAClassifierproperties file

D10. Testing the Re-trained Classifier. To assess the accuracy of there-trained RDP classifier, multiple controlled tests were performedusing 16S rRNA gene sequences from the training set and from Genbank.

D10a. Initial Testing. All sequences from Staphylococcus epidermidis andStaphylococcus aureus from the training set were compiled into twogroups. Each set of sequences was classified using the re-trainedclassifier. Initial statistical analyses indicated that 23% of the S.aureus, and 50% of the S. epidermidis sequences were assignedincorrectly at the species level using full set.

Species Correctly assigned Sequences Input Sequences S. aureus 281(76.8%) 366 S. epidermidis 116 (49.8%) 233

D10b. Optimizing the Staphylococcus training set. To assess whether themisclassifications could be attributed to erroneous designations in thetraining taxonomy, the RDP training set was checked by first clusteringthe sequences at 97% threshold using UCLUST and the highest qualitysequence from each cluster was checked against the Genbank 16S rRNAsequence database (Bacteria and Archaea) by BLAST. The top hit wasidentified and compared to the original RDP assignment. Sequences withnon-matching taxonomic assignments were removed from the training setand the classifier was re-trained. Further testing revealed that thissignificantly improved the classification; now, 96.1% of S aureus and89.5% of S. epidermidis sequences are accurately classified to thespecies-level.

Species Correctly assigned Sequences Input Sequences S. aureus 274(96.1%) 285 S. epidermidis  86 (89.5%) 96

E. Additional analysis of Staphylococcus sequences. For sequences thatwere assigned to Staphylococcus but had species assignment at <0.80confidence level, the investigators dereplicated the sequences at 97%similarity threshold using UCHIME, then manually extractedrepresentative sequences of each cluster from the dereplication,verified if they were S. aureus using BLAST. This showed that sequencesassigned to S. aureus <0.80 and S. auricularis <0.80 were S. aureus,which we included as S. aureus sequences in subsequent analysis.

Nasal Microbiome Analyses

Definitions and Metrics

Nasal community state type (i.e., nasal CST): The major nasal microbiotaprofiles, as identified by hierarchal clustering.

Nasal bacterial density: The amount of nasal bacteria present in anindividual's nasal cavity, which in this study was estimated based onthe total number of 16S rRNA gene copies detected per swab.

Prevalence: The proportion of study population found to have a variableof interest, such as a particular nasal CST or nasal bacterial taxon.

Proportional abundance: Proportion of an individual's nasal microbiotacomprised a specific nasal bacterial taxon. Using thetaxonomically-classified sequence data, we calculated the proportionalabundance for each nasal bacterial taxon as: (Number of sequencesassigned to the taxon from the sample)/(Total number of sequences fromthe sample).

Absolute abundance: The counts of a specific nasal bacterial taxoncomprising an individual's nasal microbiota. We combined proportionalabundance with nasal bacterial density to calculate taxon absoluteabundance as: (Proportional abundance of the taxon from thesample)×(nasal bacterial density of the sample).

Nasal microbiota composition: An individual's nasal microbiotacharacterized by the nasal bacterial taxa present, reported in eitherproportional abundance or absolute abundance.

Presence/absence of S. aureus by sequencing: Detection of >=2 sequencesassigned to S. aureus is categorized as presence of S. aureus bysequencing, whereas singletons or no S. aureus sequences are categorizedas absence. Detection of S. aureus by sequencing is affected by hightotal nasal bacterial density. S. aureus sequences may also be assignedincorrectly by our custom RDP species-level classifier if the S. aureussequence type is missing or underrepresented in our training set.

Staphylococcus aureus absolute abundance: Absolute abundance of S.aureus is calculated as the product of nasal bacterial density andproportional abundance of S. aureus. The assessment of S. aureus bysequencing is affected by high total nasal bacterial density. S. aureussequences may also be assigned incorrectly by our custom RDPspecies-level classifier if the S. aureus sequence type is missing orunderrepresented in our training set.

Ecological Analyses

1. Characterization of nasal bacterial density. We reported the range,median, and inter-quartile range of participants' nasal bacterialdensity, calculated using R (version 3.0.1). Boxplots of nasal bacterialdensity for each nasal CST was also generated using R.

2. Assignment of nasal community state types. To identify communitystate types (CSTs), the investigators used proportional abundance data(Euclidean distance) in hierarchal clustering by Ward linkage usingcutree through an iterative process as previously described. Comparisonsof the 6-, 7-, and 8-CST solutions revealed that seven-CST solution tobe the most parsimonious and effective. Heatmap visualization was thengenerated using nasal microbiota composition (in proportional abundance)from each participant, grouped by nasal CST assignment (FIG. 1B).

3. Identification of indicator taxa for nasal community state types. Weidentified the nasal bacterial taxa uniquely associated with each nasalCST using indicator analysis from the labdsv package (R package version1.6-1). The indicator species analysis is an objective assessment of aparticular taxon's representation of an environment or a study group. Ataxon's indicator value (IV) for a study group is determined based onits proportional abundance and prevalence in the given study group. TheIV ranges from 0 to 1, with 0 as no indication to 1 as perfectindication. To test the null hypothesis of no difference between ourobservation and what can be observed by chance, IV null distributionswere built by Monte Carlo procedure using 1,000 resampled datasets withrandomized study group assignments. The P-value for each observed IV wasdetermined based on its location within the null distribution andadjusted for false-discovery. A significance level of P=0.10 was usedand results are shown in Table 2.

4. Association between host genetics and nasal microbiota composition.The investigators assessed the correlation between nasal microbiotacomposition and host genetics based on nasal CST concordance in twinpairs and difference in pairwise ecological distance between twin types.The investigators calculated the nasal CST concordance for monozygoticand dizygotic twin pairs, where a twin pair having identical nasal CSTassignments marks concordance. The investigators computed the pairwiseecological distance among all study participants based on the nasalmicrobiota composition (proportional abundance) in three distancemetrics: Jaccard's, Bray-Curtis, and Euclidean. Using a bootstrap-basedapproach, the investigators calculated the difference in pairwisedistance in three experiments of 1,000 iterations: a)PairwiseDist_(MZ (Male or Female))-PairwiseDist_(DZ (Any Sex)), b)PairwiseDist_(MZ (Male or Female))-PairwiseDist_(DZ (Same Sex)), and C)PairwiseDist_(MZ (Male or Female))-PairwiseDist_(Random pair (Same Sex)).The correlation in twin pairs would be considered statisticallysignificant if the bootstrapped 95% confidence interval of thedifference in pairwise distance does not cross zero. Results are shownin Table 4.

5. Visualization of nasal microbiota composition by nasal CST and foreach twin type. We also visualized the overall nasal microbiotacomposition by nasal CST (FIG. 1C) and for each twin type (FIGS. 2A-C)using proportional abundance data in Euclidean distance by non-metricmultidimensional scaling (nMDS), which is a non-parametric ordinationtechnique to reduce a highly multidimensional community composition datainto a two-dimensional ordination plot. The nMDS ordination andvisualization were generated using the vegan package (R package version1.17-8).

6. Association between host genetics and of nasal bacterial density. Theinvestigators assessed the correlation between nasal bacterial densityand host genetics using intra-class correlation coefficient (ICC) in R.The investigators determined correlation of nasal bacterial density(log₁₀) for monozygotic twin pairs and dizygotic twin pairs based onsex- and age-adjusted ICC. The resultant ICC represents the fraction oftotal variance that is due to variation between groups, calculated usingthe pooled mean and standard deviation; consequently, the larger theICC, the smaller the within-twin variation, and vice versa. Thecorrelation in twin pairs was statistically significant if the 95%confidence interval of the ICC does not cross zero.

7. Heritability of nasal bacterial density. A standard biometricalheritability analysis was performed for nasal bacterial density in log₁₀to estimate the relative contribution of genetic and environmentalfactors. The twin study leverages the fact that monozygotic (MZ) twinsshare all their genes, whereas dizygotic (DZ) twins share approximately50% of their genes as other types of siblings. As such, biometricalheritability analysis separates total phenotype variance (V) into fourvariance compartments: V=A+D+C+E, where A refers to additive geneticeffects, D refers to genetics effects due to dominance, C refers toshared environmental effects, and E refers to non-shared environmentaleffects.

The investigators could not simultaneously estimate the effects of D andC because they are confounded. Therefore, the investigators fittedseparate ACE and ADE models. The investigators also fitted sub-modelsAE, DE, CE, and E, as the simpler models may sufficiently explain thedata. The investigators chose the non-nested model with the lowestAkike's Information Criteria (AIC), and the investigators selected themost parsimonious nested model with χ² likelihood ratio p>0.05. Allanalyses were performed using the statistical package R (version 3.0.2)and the R package mets: Analysis of Multivariate Event Times (version0.2.6).

After testing the assumptions of equal regression, intercept, andresidual variance for twin 1 and twin 2 as well as for MZ and DZ twins,the investigators found that the ADE model had the lowest AIC and thatit could be further reduced to a AE model because of its lower loglikelihood ratio; however, the AE model could not be reduced to an Emodel (Table 3). Taken together, these results showed both heritabilityand non-shared environmental influences on nasal bacterial density, witha smaller heritability effect (29.8%, 95% Cl: 6%-54%) and a largernon-shared environmental effect (70.1%, 95% Cl: 46%-94%).

Of note, the final and intermediate models, as shown in Table 5 includedadjustment for sex and age. While age was not associated with nasalbacterial density and its inclusion had no significant impact onmodeling outcome, sex emerged as a significant factor as reported in themain text.

8. Association between nasal bacterial density and host factorsincluding sex. The median and quantile of nasal bacterial density bysex, history of atopic disease and psoriasis, and by current smokingstatus were calculated using R. We also plotted the nasal bacterialdensity (log₁₀) as scattered plots with median (FIG. 5A). Difference innasal bacterial density based on each host factor was compared using twonon-parametric tests: the Wilcoxon-ranked sum and Kolmogorov-Smirnovtest, with a significance level of α=0.05, with results as shown inTable S5.

To determine if the significant sex difference in nasal bacterialdensity could be explained by CST prevalence, the nasal CST prevalencefor men versus women is as shown in Table 3, which we compared by χ²test. The investigators further assessed if men and women havesignificantly different nasal bacterial density, irrespective of nasalCST using quasi-Poisson model comparing the outcome of nasal bacterialdensity, stratified by the seven nasal CSTs. Women with CST3 was used asthe reference and the results are shown in Table S6, which showed thatmen and women had significantly different nasal bacterial density evenafter adjusting for nasal CST.

9. Association of nasal bacterial density with microbiota composition:The investigators compared the nasal bacterial density across CSTs byanalysis of variance (ANOVA) in R and reported the median nasalbacterial density and interquartile range for each nasal CST in Table 3.The significant difference in sex-adjusted nasal bacterial densityacross nasal CSTs can also be seen in Table 7.

10. Decision tree analysis: Using decision tree analysis with recursivepartitioning and splitting by information criteria using the rpartpackage, a derivation model was built used a simulated population of 100randomly-drawn (without replacement) individuals. Using the derivationset, two outcomes were determined: S. aureus presence/absence and S.aureus absolute abundance (log₁₀) in five categories (Category 1-5).Among the nasal bacterial taxa detected, those significantly associatedwith S. aureus nasal colonization were incorporated in the derivationmodel, which included taxa with conflicting associations in earlierstudies. The derivation decision tree model incorporated the absoluteabundances (log₁₀) of the following nasal taxa: Anaerococcus,Finegoldia, Peptoniphilus, Dolosigranulum, Corynebacterium, UnclassifiedCorynebacteriaceae, Propionibacterium acnes, Propionibacteriumgranulosum, Simonsiella <0.80, Staphylococcus epidermidis (including<0.80), and Moraxella.

A model was derived for each outcome of interest and the branches weretrimmed down to include only those with 10 or more individuals in eachterminal node (except for Simonsiella<0.80, which was an early 2^(nd)node). A predicted outcome was assigned to each terminal node (i.e., aspredicting either S. aureus presence or absence or as predicting a S.aureus absolute abundance category) (FIGS. 5A and 6A).

Validation test for the predicative thresholds was conducted using 10additional simulated populations of 100 randomly-drawn (withoutreplacement) individuals. The validation results were determined tosupport the initial model if the predicative thresholds produced resultsthat are more similar to the predicted outcome than the underlyingsimulated population (FIGS. 5B and 6B-C).

11. Correlation between S. aureus absolute abundance and cultureoutcome. The investigators calculated S. aureus absolute abundance amongnon-CST1 individuals with S. aureus detectable by DNA sequencing. Theinvestigators divided these individuals into four categories based onten-fold differences in S. aureus absolute abundance (<10⁴, 10⁴-<10⁵,10⁵-<10⁶, 10⁶-10⁷). We plotted the histograms of each S. aureus absoluteabundance category in men and women (FIG. 5B), which showed that womenmost often fell into to two lowest absolute abundance categories (<10⁴and 10⁴-<10⁵) while men were more likely to have the middle twocategories (10⁴-<10⁵ and 10⁵-<10⁶). The correlation between S. aureusnasal culture and S. aureus absolute abundance category was shown inFIG. 6C. The relationship between S. aureus nasal culture (outcome) toother variables including S. aureus absolute abundance category, sex,history of atopic disease and psoriasis, and current smoking status wasassessed using a multivariate linear regression model, which showed thatsex was not a significant predictor of S. aureus culture outcome(P=0.79), after adjusting for S. aureus absolute abundance category(P<0.001), where the model indicated that with each ten-fold increase inS. aureus absolute abundance, the probability of having a positive S.aureus culture increases by 30.4% (F-statistic 7.19 on 68 degrees offreedom, Model P<0.001).

TABLE 6 Kolmogorov- Inter-Quartile Range Wilcoxon Smimov Median 25th75th p-value p-value Overall 4.07E+06 7.08E+06 n/a n/a Sex Women (n =102) 2.97E+06 1.33E+06 9.11E+06 Men (n = 76) 7.94E+06 2.20E+06 4.30E+07Difference p < 0.001 p = 0.005 History of atopic diseases Yes (n = 54)4.46E+06 1.90E+06 1.50E+07 No (n = 124) 4.39E+06 1.50E+06 1.80E+07Difference p = 0.47  p = 0.35  History of psoriasis Yes (n = 15)6.41E+06 4.80E+06 2.10E+07 No (n = 158) 3.69E+06 1.57E+06 1.63E+07Difference p = 0.22  p = 0.12  Current smoker Yes (n = 33) 3.23E+061.66E+06 9.59E+06 No (n = 145) 4.44E+06 1.59E+06 1.96E+07 Difference p =0.61  p = 0.53 

TABLE 7 Men*** Women*** CST1** 1.20E+07 4.68E+06 (S. aureus) CST2***8.72E+07 3.04E+07 (Enterobacteriaceae) CST3*** 4.95E+06 2.03E+06 (S.epidermidis) (Reference) CST4*** 2.26E+07 8.51E+06 (Propionibacterium)CST5 9.30E+06 3.68E+06 (Corynebacterium) CST6* 1.58E+07 6.09E+06(Moraxella) CST7 9.87E+06 3.90E+06 (Dolosigranulum)

REFERENCES

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What is claimed is:
 1. A method of treating Staphylococcus aureus nasalcolonization, the method comprising the steps of: collecting a nasalswab sample from a subject; extracting nucleic acid from the nasal swabsample; sequencing the extracted nucleic acid to generate sequence data;analyzing the sequence data to determine an abundance of Dolosigranulumspecies represented as rRNA gene copies in the nasal swab sample;determining that the abundance of Dolosigranulum rRNA is below athreshold level of 1.2×10⁶ gene copies in the nasal swab samplecollected from the subject; identifying the subject as requiringtreatment for Staphylococcus aureus nasal colonization based on theabundance of Dolosigranulum rRNA being below the threshold level; andadministering a pharmaceutical composition to the subject to treat theStaphylococcus aureus nasal colonization, wherein the pharmaceuticalcomposition comprises a therapeutically effective amount of at least oneprobiotic organism, and the at least one probiotic organism comprisesDolosigranulum species.
 2. The method of claim 1, wherein at least aportion of the Staphylococcus aureus is resistant to methicillin.
 3. Themethod of claim 1, further comprising administering at least oneantibiotic to the subject.
 4. The method of claim 3, wherein the atleast one antibiotic comprises mupirocin.
 5. The method of claim 1,wherein the pharmaceutical composition comprises at least onepharmaceutically acceptable carrier.
 6. The method of claim 5, whereinthe at least one pharmaceutically acceptable carrier comprises a growthmedium to sustain the at least one probiotic organism prior toadministration to the subject.
 7. The method of claim 1, wherein thepharmaceutical composition is intranasally administered to the subject.8. The method of claim 1, wherein the Dolosigranulum species isDolosigranulum pigrum.
 9. The method of claim 1, wherein thepharmaceutical composition further comprises a therapeutically effectiveamount of a Corynebacterium species.
 10. The method of claim 9, whereinthe Corynebacterium species is Corynebacterium pseudodiphtheriticum. 11.A method of treating Staphylococcus aureus nasal colonization, themethod comprising the step of: administering a pharmaceuticalcomposition to a subject in need of treatment for Staphylococcus aureusnasal colonization, wherein the subject exhibits an abundance ofDolosigranulum rRNA below a threshold level of 1.2×10⁶ 16S rRNA genecopies in a nasal swab sample of the subject, and wherein thepharmaceutical composition comprises a therapeutically effective amountof at least one probiotic organism, and the at least one probioticorganism comprises Dolosigranulum species, thereby treating theStaphylococcus aureus nasal colonization.
 12. The method of claim 11,wherein at least a portion of the Staphylococcus aureus is resistant tomethicillin.
 13. The method of claim 11, further comprisingadministering at least one antibiotic to the subject.
 14. The method ofclaim 13, wherein the at least one antibiotic comprises mupirocin. 15.The method of claim 11, wherein the pharmaceutical composition comprisesat least one pharmaceutically acceptable carrier.
 16. The method ofclaim 15, wherein the at least one pharmaceutically acceptable carriercomprises a growth medium to sustain the at least one probiotic organismprior to administration to the subject.
 17. The method of claim 11,wherein the pharmaceutical composition is intranasally administered tothe subject.
 18. The method of claim 11, wherein the Dolosigranulumspecies is Dolosigranulum pigrum.
 19. The method of claim 11, whereinthe pharmaceutical composition further comprises a therapeuticallyeffective amount of a Corynebacterium species.
 20. The method of claim19, wherein the Corynebacterium species is Corynebacteriumpseudodiphtheriticum.